CN112234604B - Multi-energy complementary power supply base optimal configuration method, storage medium and equipment - Google Patents
Multi-energy complementary power supply base optimal configuration method, storage medium and equipment Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
- H02J2300/22—The renewable source being solar energy
- H02J2300/24—The renewable source being solar energy of photovoltaic origin
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
- H02J2300/28—The renewable source being wind energy
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/40—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation wherein a plurality of decentralised, dispersed or local energy generation technologies are operated simultaneously
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/50—Photovoltaic [PV] energy
- Y02E10/56—Power conversion systems, e.g. maximum power point trackers
Abstract
The invention discloses a multi-energy complementary power supply base optimal configuration method, a storage medium and equipment, wherein basic data of a composite power station, power plant data in the composite power station and operation prediction data of the composite power station are obtained from relevant departments of a power supply base and a power system; constructing a multi-energy complementary power supply optimizing configuration model target by taking the multi-aspect comprehensive cost of the minimum composite power station planning operation as an objective function; constructing constraint conditions of optimal configuration of the composite power station; based on the established objective function and the established optimal configuration constraint condition of the composite power station, inputting the acquired data into an optimal configuration model, and solving to obtain a configuration result of the composite power station. The invention aims at minimizing comprehensive cost in multiple aspects, fully considers the internal strategy and external characteristics of the power supply base, the whole power station and the unit characteristics, and has physical authenticity and mathematical simplicity of the optimization problem, so that the optimization configuration of the complementary power supply in the power supply base can be rapidly and accurately solved, and the invention has guiding significance for planners.
Description
Technical Field
The invention belongs to the technical field of power supply planning, and particularly relates to an optimal configuration method, storage medium and equipment for a multi-energy complementary power supply base, which are used for determining a reasonable configuration scheme of the multi-energy complementary power supply in the power supply base.
Background
The rapid development of new energy sources, and the phenomena of wind abandon, light abandon and water abandon of power supply bases raise high attention. Along with the trend of diversification development of power supplies, the advantages of enrichment of multiple types of resources by various large power supply bases in China are relied on, and the cooperative development of multiple types of complementary power supplies to optimize the outgoing characteristics of the power supply bases becomes a current widely focused problem. Therefore, a multi-energy complementary power capacity optimizing configuration method is needed to optimize the energy structure and improve the new energy consumption.
The existing research on the optimal configuration of the multi-energy complementary power supply optimizes the capacity of the complementary system from different complementary angles, and determines the production scale of each type of equipment. The problem is that these studies are only based on the complementary development of specific wind-light-water, wind power-light-heat or wind power-pumping and storage, and the like, and the application has limitations. In order to accommodate the increase in the types of complementary power sources, a more general optimization configuration method is to be studied.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a multi-energy complementary power supply base optimal configuration method, a storage medium and equipment aiming at the defects in the prior art, and to put forward the concept of a composite power station, and to establish a multi-energy complementary power supply optimal configuration model comprehensively considering resource conditions, multi-energy complementary characteristics of a system and external planning requirements so as to meet the requirements of planning personnel on economy, reliability, environmental protection, flexibility and power supply complementarity.
The invention adopts the following technical scheme:
a multi-energy complementary power supply base optimal configuration method comprises the following steps:
s1, acquiring basic data of a composite power station, power plant data in the composite power station and operation prediction data of the composite power station from relevant departments of a power supply base and a power system;
s2, constructing a multi-energy complementary power supply optimizing configuration model target by taking the multi-aspect comprehensive cost of the minimum composite power station planning operation as an objective function;
s3, constructing a composite power station planning decision constraint condition, a composite power station overall operation constraint condition, an intermittent power supply operation constraint in the composite power station, a flexible power supply operation constraint in the composite power station and an external characteristic constraint of the composite power station;
s4, inputting the data acquired in the step S1 into an optimal configuration model based on the objective function established in the step S2 and the optimal configuration constraint condition of the composite power station established in the step S3, and solving to obtain a configuration result of the composite power station.
Specifically, in step S1, the composite power station basic data includes: capacity Cap of outgoing channel line The method comprises the steps of carrying out a first treatment on the surface of the Minimum utilization μ of intermittent resources; planned output curve of composite power station
Compounding power plant data within a power plant, comprising: the number K of units of each power plant; unit investment cost C of each power plant unit inv And unit operation cost C ope The method comprises the steps of carrying out a first treatment on the surface of the Operating parameters of each power plant unit; composite plant operation prediction data comprising: incoming call quantity W of hydropower station; predicted output curve P of wind farm pre,WT (t); predicted output curve P of photovoltaic power station pre,PV (t)。
Specifically, in step S2, the target V of the multi-energy complementary power supply optimizing configuration model is:
wherein ,ΩC A set of power plants to be built;
K i respectively representing the number of units to be built and all available units of the ith power plant; CRF (Cryptographic CRF) i A funds recovery coefficient for the ith power plant; />
The investment cost and the operation cost of a single unit of the ith power plant are respectively determined by the output states of the power plants; />
The cost is checked for the output deviation of the h composite power station, and the specific calculation method is described in detail below; t is the analog duration.
Specifically, in step S3, constraint conditions of the composite power station planning decision include resource condition constraint; the integral operation constraint conditions of the composite power station comprise the constraint of the range of the output power of the composite power station and the constraint of a multi-energy complementary operation strategy; the intermittent power source operation constraint in the composite power station comprises wind power station operation constraint and photovoltaic power station operation constraint; the flexible power supply operation constraint in the composite power station comprises the operation constraint of a thermal power unit, the operation constraint of a hydroelectric unit, the operation constraint of an energy storage element and the operation constraint of a photo-thermal power station; external characteristic constraints of a composite power station include capacity characteristics, electrical characteristics, reliability, flexibility, and environmental friendliness.
Further, the composite plant's outgoing power range constraint is expressed as:
wherein ,
the output of the composite power station at the time h;
the multi-energy complementary operating strategy constraints include:
the peak shaving characteristic constraint is expressed as:
wherein ,
checking the cost for the output deviation of the composite power station at the time h; lambda (P) is the unit power deviation checking cost of the composite power station, and a sectional checking mode is adopted, so that the larger the output deviation is, the higher the corresponding checking cost is; />
The planned output at the time h; delta max Representing a set allowable maximum force deviation;
the fluctuation-characteristic constraint is expressed as:
wherein ,Capline The capacity of an outgoing channel of the composite power station; epsilon is the proportion of the maximum allowable transmission power variation of the composite power station in unit time to the transmission capacity of the transmission channel;
intermittent new energy consumption constraints are expressed as:
wherein ,ΩIP Is a collection of intermittent power sources; t is the simulation time length; μ is the minimum utilization of intermittent resources;
predicted output of the power plant i at the time h;
the outgoing channel minimum utilization constraint is expressed as:
wherein ,
is the minimum annual average utilization rate of the outgoing channel.
Further, the operational constraints of wind farms and photovoltaic power plants are expressed as:
wherein ,vh 、I h Respectively representing the wind speed and the illumination intensity at the time h;
respectively representing power characteristic conversion functions of wind power and photovoltaic; />
Respectively representing the abandoned wind and the abandoned light power of the power plant i at the time h; omega shape WT 、Ω PV Representing a collection of wind farms and photovoltaic power plants, respectively.
Further, the capacity characteristics are expressed as:
wherein ,CapCPP,credit Is the confidence capacity of the composite power station; b (B) peak Is a set of peak-to-load periods; t (T) peak Is the duration of the peak charge period;
the charge characteristics are expressed as:
wherein ,ECPP Generating power of the composite power station in the simulation period;
reliability is expressed as:
wherein ,XCPP The output state variable is the output state variable of the composite power station;
representing the s-th output state of the composite power station;
indicating the output state of the composite power station as +.>
Probability of (2); NS (NS) CPP The number of output states of the composite power station;
flexibility includes:
climbing capacity, specifically:
wherein ,Bup A set representing a load rising period; t (T) up Indicating the length of the load rising period.
Climbing ability, in particular
wherein ,Bdown A set representing a load-down period; t (T) down A length representing a load-falling period;
providing positive standby capability, specifically:
wherein ,Bpeak A set representing load peak-to-load periods; t (T) peak Representing the length of the load peak-to-load period; omega shape FP Representing a set of flexible power plants;
representing the maximum output force which can be provided by the ith power plant at the time h;
providing negative standby capability, specifically:
wherein ,Bvalley Representing a set of load valley periods; t (T) valley Representing the length of the load valley period;
representing the minimum output force which can be provided by the ith power plant at the time h;
the environmental protection is as follows:
wherein ,
representing the emission of the composite plant pollutant x during the simulation period; omega shape F Is a collection of fuel power sources; f (P) i,h ) A fuel consumption characteristic function of the power plant i; o (O) i,x Is the emission equivalent of the pollutant x of the power plant i.
Specifically, in step S4, the solving result includes: the method comprises the steps of generating a unit production scheme of each power plant to be selected in a composite power station, generating power of each power plant in the composite power station in a simulation period, and planning and running costs of the composite power station; after the exact configuration and operating strategy of the composite power station is obtained, the capacity characteristics, the electric quantity characteristics, the reliability, the flexibility and the environmental protection of the composite power station are calculated.
Another aspect of the invention is a computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a computing device, cause the computing device to perform any of the methods.
Another aspect of the present invention is a computing device, including:
one or more processors, memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs comprising instructions for performing any of the methods.
Compared with the prior art, the invention has at least the following beneficial effects:
aiming at the problem of optimal configuration of the multi-energy complementary power supply base, the intermittent power supply and the flexible power supply in the power supply base are bundled and optimized and equivalent to a composite power station. Based on the operation characteristics of various power supplies, the method for optimizing the configuration based on the composite power station is provided by considering the influence of resource conditions, the system multipotency complementary characteristics and the external conveying capacity requirements, so that the power supply base externally presents a comprehensive technical characteristic which is better than a single power supply structure or two-by-two complementary, the economical efficiency of the complementary system is also realized, and the method has important guiding significance for planning the power supply base under the high-proportion grid connection and multipotency complementary background of new energy.
Furthermore, the data is collected according to the listed data list, so that the comprehensive collection of the data required by the invention can be completed, and the smooth proceeding of the subsequent steps is ensured.
Further, in consideration of various costs of the composite power station in the construction and operation processes, an optimization function aiming at minimizing comprehensive costs in multiple aspects is established, so that the optimal configuration of various power supplies is economically optimal.
Further, based on various power supply characteristics and system planning requirements, linear constraint conditions considering the internal strategy and external characteristics of the composite power station and the characteristics of the whole power station and the unit are constructed, and physical characteristics are fully reflected while mathematical calculation is simplified.
Further, in consideration of the transmission capacity of the connecting lines between the composite power station and the external power grid, each connecting line is simplified and processed into a unified outgoing channel, and the capacity of the outgoing channel is used for limiting the outgoing power of the composite power station.
Furthermore, in order to fully reflect the fluctuation of wind energy and photovoltaic resources in the optimization process, the relation between the generated energy of the new energy and the abandoned electric quantity is characterized, and the operation of a wind power station and a photovoltaic power station is restrained.
Furthermore, in order to reduce the calculation scale, the operation result of the composite power station under the given operation strategy is counted, a simplified calculation method of indexes such as electric quantity, capacity, climbing and the like is provided, and the external characteristics of the composite power station are restrained for being selected by planning personnel for use.
Further, after the mixed integer linear programming model constructed by the invention is solved to obtain the production and operation results of the unit, the capacity characteristic, the electric quantity characteristic, the reliability, the flexibility and the environmental protection of the composite power station as a whole are required to be calculated, and the indexes provide guidance for the large-system power supply planning of the composite power station.
In summary, the invention aims at minimizing comprehensive cost in multiple aspects, fully considers the internal strategy and external characteristics of the power supply base, the whole power station and the unit characteristics, and combines the physical authenticity and mathematical simplicity of the optimization problem, can rapidly and accurately solve the optimal configuration of the complementary power supply in the power supply base, and has guiding significance for planners.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a graph of the four seasons typical sunrise force of a hydropower-wind power-photovoltaic composite power station, wherein (a) is a spring typical day curve, (b) is a summer typical day curve, (c) is an autumn typical day curve, and (d) is a winter typical day curve;
fig. 3 shows a four-season typical sunrise force curve of a photovoltaic-photo-thermal composite power station, wherein (a) is a spring typical day curve, (b) is a summer typical day curve, (c) is an autumn typical day curve, and (d) is a winter typical day curve.
Detailed Description
Referring to fig. 1, the method for optimizing and configuring a multi-energy complementary power supply base of the present invention includes the following steps:
s1, acquiring required data from a power supply base and related departments of a power system;
composite plant base data comprising: capacity Cap of outgoing channel line The method comprises the steps of carrying out a first treatment on the surface of the Minimum utilization μ of intermittent resources; planned output curve of composite power station
Compounding power plant data within a power plant, comprising: the number K of units of each power plant; unit investment cost C of each power plant unit inv And unit operation cost C ope The method comprises the steps of carrying out a first treatment on the surface of the And operating parameters of each power plant unit.
Composite plant operation prediction data comprising: incoming call quantity W of hydropower station; predicted output curve P of wind farm pre,WT (t); predicted output curve P of photovoltaic power station pre,PV (t)。
S2, constructing a multi-energy complementary power supply optimizing configuration model target by taking the multi-aspect comprehensive cost of the minimum composite power station planning operation as an objective function;
wherein ,ΩC A set of power plants to be built;
K i respectively representing the number of units to be built and all available units of the ith power plant; CRF (Cryptographic CRF) i A funds recovery coefficient for the ith power plant; />
The investment cost and the operation cost of a single unit of the ith power plant are respectively determined by the output states of the power plants; />
The cost is checked for the output deviation of the h composite power station, and the specific calculation method is described in detail below; t is the analog duration.
S3, constructing constraint conditions of optimal configuration of the composite power station;
s301, constraint conditions of composite power station planning decision comprise:
the constraint of the resource condition, namely that the newly increased number of each power plant is limited by regional land environment resources and the like, is expressed as:
wherein ,
representing the minimum and maximum newly increased numbers of ith power plants, respectively.
S302, constructing an operation constraint condition of the whole composite power station, wherein the operation constraint condition comprises the following steps:
1) The outgoing power range constraint of the composite power station:
the transmission power of the composite power station at each moment should not exceed the transmission capacity of the transmission channel, and can be expressed as:
wherein ,
the output of the composite power station at the moment h is calculated according to the following formula:
wherein i is the power plant number; n is a power plant in the composite power station; p (P) i,h The output of the power plant i in the composite power station at the time h is obtained.
2) A multi-energy complementary operating strategy constraint comprising:
(1) Peak shaving characteristic constraint:
in the aspect of peak regulation characteristics, from the scheduling point of view, the output deviation checking cost is introduced, so that the output of the composite power station is required to be changed according to a given planned output curve. And the output deviation of the composite power station is limited not to exceed the set maximum output deviation. The expression is as follows:
wherein ,
checking the cost for the output deviation of the composite power station at the time h; lambda (P) is the unit power deviation checking cost of the composite power station, and a sectional checking mode is adopted, so that the larger the output deviation is, the higher the corresponding checking cost is; />
The planned output at the time h; delta max Indicating the set allowable maximum force deviation.
(2) Wave characteristics constraint:
in the aspect of fluctuation characteristics, the fluctuation rate change of the output of the composite power station from moment to moment is smaller than a certain limit value, and can be expressed as:
wherein ,Capline The capacity of an outgoing channel of the composite power station; epsilon is the ratio of the maximum allowable output power variation of the composite power station in unit time to the transmission capacity of the output channel.
(3) Intermittent new energy consumption constraint:
in terms of intermittent new energy consumption, the utilization rate of intermittent resources such as wind power, photovoltaic and the like needs to meet the system requirement, and can be expressed as follows:
wherein ,ΩIP Is a collection of intermittent power sources; t is the simulation time length; μ is the minimum utilization of intermittent resources;
the predicted output of the power plant i at the time h is obtained.
(4) Minimum utilization constraint of outgoing channel:
in terms of the utilization of the outgoing channel, the annual outgoing power of the composite power station needs to meet the minimum annual average utilization requirement of the outgoing channel, expressed as:
wherein ,
is the minimum annual average utilization rate of the outgoing channel.
S303, constructing intermittent power supply operation constraint in composite power station
For wind farms and photovoltaic power plants, the effect of wind and light abandoning needs to be considered, and the operation constraint is expressed as:
wherein ,vh 、I h Respectively representing the wind speed and the illumination intensity at the time h;
respectively representing power characteristic conversion functions of wind power and photovoltaic; />
Respectively representing the abandoned wind and the abandoned light power of the power plant i at the time h; omega shape WT 、Ω PV Representing a collection of wind farms and photovoltaic power plants, respectively.
S304, constructing flexible power supply operation constraint in composite power station
1) Operation constraint of thermal power generating unit
The operation constraint of the thermal power generating unit mainly comprises: force range constraint, climbing rate constraint, start-stop time constraint, utilization hour constraint, and the like.
2) Operation constraint of hydroelectric generating set
The hydroelectric generating set is subjected to simulated scheduling for a period of months, and general operation constraints comprise: output range constraint, monthly water power range constraint, monthly stored power range constraint, power change coupling constraint, power balance constraint and the like.
3) Operational constraints for energy storage elements
Operational constraints of energy storage power stations generally include: energy storage and generation power range constraints; mutual exclusion constraint of power generation and energy storage states; time sequence change range constraint of energy storage electric quantity; periodic stored energy power balance constraints, and the like.
(4) Operating constraints for photo-thermal power stations
The photo-thermal power station is used as an emerging renewable resource, has flexible regulation capability, and the operation constraint mainly comprises the energy flow constraint of each subsystem in the power station and the power generation capacity constraint of the photo-thermal power station.
S305, constructing external characteristic constraint of composite power station
The external characteristic is a statistical index of the operation result of the composite power station with a given operation strategy, and if the system planner has further requirements on the external characteristic, the corresponding range constraint can be increased on the characteristic index, including:
1) Capacity characteristics;
the capacity of the composite power station can be estimated by using the confidence capacity, and the invention adopts the average output of the peak load period as the confidence capacity of the composite power station to characterize the power supply capacity, which can be expressed as:
wherein ,CapCPP,credit Is the confidence capacity of the composite power station; b (B) peak Is a set of peak-to-load periods; t (T) peak Is the duration of the peak-to-load period.
2) The electrical quantity characteristics;
the electrical characteristics of a composite power station are used to represent the capability of the composite power station to provide electrical power from various sources that make up the composite power station, which can be expressed as:
wherein ,ECPP The power generation amount of the composite power station in the simulation period is obtained.
3) Reliability;
the method comprises the steps of equivalently using a composite power station as a unit, acquiring probability levels of various output states of the composite power station based on long-term statistical characteristics, and establishing a multi-state unit model of the composite power station, wherein the multi-state unit model can be expressed as:
wherein ,XCPP The output state variable is the output state variable of the composite power station;
representing the s-th output state of the composite power station;
indicating the output state of the composite power station as +.>
Probability of (2); NS (NS) CPP The number of output states of the composite power station is the number.
4) Flexibility;
the flexibility of a composite plant is generally used to evaluate the benefits of the composite plant at the system regulatory level, mainly consisting of:
(1) Climbing ability
The ascending slope capability of the composite power station is characterized by adopting an average value of the output increase of the composite power station in the load ascending period:
wherein ,Bup A set representing a load rising period; t (T) up Indicating the length of the load rising period.
(2) Climbing ability
The downhill climbing capability of the composite power station is characterized by adopting an average value of the output reduction of the composite power station in the load descending period:
wherein ,Bdown A set representing a load-down period; t (T) down Indicating the length of the load-falling period.
(3) Providing positive standby capability
The average of the sum of positive backup capacity provided by peak load period flexible power plants is used to characterize the capacity of a composite power station to provide positive backup:
wherein ,Bpeak A set representing load peak-to-load periods; t (T) peak Representing the length of the load peak-to-load period; omega shape FP Representing a set of flexible power plants;
indicating the maximum power that the ith power plant can provide at time h.
(4) Providing negative standby capability
The average of the sum of the capability of the valley load period flexible power plant to provide negative backup is used to characterize the capability of the composite power plant to provide negative backup:
wherein ,Bvalley Representing a set of load valley periods; t (T) valley Representing the length of the load valley period;
indicating the minimum power available from the ith power plant at time h.
5) Environmental protection;
for a composite power station without a fuel power source, the composite power station can be considered as a clean power source, and no pollutant emission is generated. For a composite power station containing a fuel power source, the environmental protection property of the composite power station is characterized by the emission of various pollutants:
wherein ,
representing the emission of the composite plant pollutant x during the simulation period; omega shape F Is a collection of fuel power sources; f (P) i,h ) A fuel consumption characteristic function of the power plant i; o (O) i,x Is the emission equivalent of the pollutant x of the power plant i.
S4, inputting the data in the step S1 into an optimal configuration model based on the optimization function established in the step S2 and the constraint condition established in the step S3, and solving to obtain a configuration result of the composite power station.
The solving result comprises the following steps: the method comprises the steps of generating a unit production scheme of each power plant to be selected in a composite power station, generating power of each power plant in the composite power station in a simulation period, and planning and running costs of the composite power station; the planning scheme realizes the optimal economical efficiency of the complementary system under the conditions of meeting the resource condition of the composite power station, the multi-energy complementary characteristic of the system and the external planning requirement.
After the exact configuration and operation strategy of the composite power station are obtained, the capacity characteristic, the electric quantity characteristic, the reliability, the flexibility and the environmental protection of the composite power station can be calculated through (12) to (19), so that the power supply base externally presents a relatively single power supply structure or two-by-two complementary better comprehensive technical characteristics, and the novel energy consumption and utilization are facilitated.
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the invention, as presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The simulation is carried out by taking a hydropower-photovoltaic-wind power and photovoltaic-photo-thermal two-type clean energy composite power station which is planned to be cooperatively developed by a certain energy base in the south of certain province in China as an object. The main economic parameters of each unit are shown in table 1. To meet the complementarity requirement, the complementary configuration parameters of the composite plant are shown in table 2.
TABLE 1 major economic parameters for various power sources in a composite plant
Table 2 complementary configuration parameters for a composite plant
According to the parameters and the provided optimal configuration model of the composite power station, the optimal configuration results of the two types of composite power stations can be obtained through solving, and are shown in the table 3:
as can be seen from table 3, the total power output of the hydropower-photovoltaic-wind power composite power station is 13.5 hundred million degrees, the utilization rate of the output channel is 38.5%, and the system output requirement is met; the total intermittent resource waste amount of the system is 5.17GWh, the utilization rate of the intermittent resource reaches 99%, and the requirement of the utilization rate of the system resource is met. The total external power supply of the photovoltaic-photo-thermal composite power station is 15 hundred million degrees, the utilization rate of an external transmission channel reaches 42.8%, and the external transmission requirement of a system is met. The total intermittent resource electricity rejection amount of the system is 2.62GWh, the intermittent resource utilization rate reaches 99%, and the requirement of the system resource utilization rate is met.
Table 3 optimal configuration results for composite plants
The four-season typical sunrise force curve of the hydropower-wind power-photovoltaic composite power station is shown in fig. 2. The flexible adjustment capability of the hydropower can be seen to effectively stabilize wind and light output fluctuation. Meanwhile, the in-day and seasonal complementarity of the wind, light and water can also improve the delivery capacity of the complementary system.
The four-season typical sunrise curve of the photovoltaic-photo-thermal composite power station is shown in figure 3. The graph shows that the photo-thermal power station can realize continuous and uninterrupted output of light and heat as a whole due to the heat storage system. In addition, the photovoltaic and photo-thermal power generation can realize peak-shifting power generation, and the complementary benefit is obvious.
The external characteristic indexes of the composite power station facing the planning are shown in table 4. It can be seen that the external characteristics of two types of composite plants vary significantly with seasonal variations, in which: the confidence capacity, the electric quantity and the lower standby capacity are all the largest in summer and the smallest in winter; the opposite is true for the change in the upper spare capacity. The up-down climbing rate is related to the scheduling curve, and the difference of seasons is not great.
Table 4 composite plant planning-oriented external characteristic index
In summary, according to the multi-energy complementary power supply base optimal configuration method, the storage medium and the equipment, aiming at the problem of optimal configuration of the multi-energy complementary power supply, intermittent power supplies and flexible power supplies in the power supply base are bundled and optimized and are equivalent to a composite power station, and the optimal configuration method for the economical efficiency of the complementary system is provided by taking the operating characteristics of various power supplies as the basis and considering the influence of resource conditions, the multi-energy complementary characteristics of the system and external planning requirements.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above is only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited by this, and any modification made on the basis of the technical scheme according to the technical idea of the present invention falls within the protection scope of the claims of the present invention.
Claims (7)
1. The optimal configuration method of the multi-energy complementary power supply base is characterized by comprising the following steps of:
s1, acquiring basic data of a composite power station, power plant data in the composite power station and operation prediction data of the composite power station from relevant departments of a power supply base and a power system;
s2, constructing a multi-energy complementary power supply optimizing configuration model target by taking the multi-aspect comprehensive cost of the minimum composite power station planning operation as an objective function;
s3, constructing a composite power station planning decision constraint condition, a composite power station overall operation constraint condition, an intermittent power supply operation constraint in the composite power station, a flexible power supply operation constraint in the composite power station and an external characteristic constraint of the composite power station, wherein a multi-energy complementary power supply optimizing configuration model target V is as follows:
wherein ,ΩC A set of power plants to be built;
K i respectively representing the number of units to be built and all available units of the ith power plant; CRF (Cryptographic CRF) i A funds recovery coefficient for the ith power plant; />
The investment cost and the operation cost of a single unit of the ith power plant are respectively determined by the output states of the power plants; />
Checking the cost for the output deviation of the composite power station at the time h; t is the simulation time length;
constraint conditions of the composite power station planning decision include resource condition constraint; the integral operation constraint conditions of the composite power station comprise the constraint of the range of the output power of the composite power station and the constraint of a multi-energy complementary operation strategy; the intermittent power source operation constraint in the composite power station comprises wind power station operation constraint and photovoltaic power station operation constraint; the flexible power supply operation constraint in the composite power station comprises the operation constraint of a thermal power unit, the operation constraint of a hydroelectric unit, the operation constraint of an energy storage element and the operation constraint of a photo-thermal power station; external characteristic constraints of the composite power station include capacity characteristics, electric quantity characteristics, reliability, flexibility and environmental friendliness, and the outgoing power range constraints of the composite power station are expressed as:
wherein ,
the output of the composite power station at the time h;
the multi-energy complementary operating strategy constraints include:
the peak shaving characteristic constraint is expressed as:
wherein ,
checking the cost for the output deviation of the composite power station at the time h; lambda (P) is the unit power deviation checking cost of the composite power station, and a sectional checking mode is adopted, so that the larger the output deviation is, the higher the corresponding checking cost is; />
The planned output at the time h; delta max Representing a set allowable maximum force deviation;
the fluctuation-characteristic constraint is expressed as:
wherein ,Capline The capacity of an outgoing channel of the composite power station; epsilon is the proportion of the maximum allowable transmission power variation of the composite power station in unit time to the transmission capacity of the transmission channel;
intermittent new energy consumption constraints are expressed as:
wherein ,ΩIP Is a collection of intermittent power sources; t is the simulation time length; μ is the minimum utilization of intermittent resources;
predicted output of the power plant i at the time h;
the outgoing channel minimum utilization constraint is expressed as:
wherein ,
the minimum annual average utilization rate of the outgoing channel;
s4, inputting the data acquired in the step S1 into an optimal configuration model based on the objective function established in the step S2 and the optimal configuration constraint condition of the composite power station established in the step S3, and solving to obtain a configuration result of the composite power station.
2. The method for optimal configuration of a multi-energy complementary power supply base according to claim 1, wherein in step S1, the basic data of the power station is compounded, including: capacity Cap of outgoing channel line The method comprises the steps of carrying out a first treatment on the surface of the Minimum utilization μ of intermittent resources; planned output curve of composite power station
Compounding power plant data within a power plant, comprising: the number K of units of each power plant; unit investment cost C of each power plant unit inv And unit operation cost C ope The method comprises the steps of carrying out a first treatment on the surface of the Operating parameters of each power plant unit; composite plant operation prediction data comprising: incoming call quantity W of hydropower station; predicted output curve P of wind farm pre,WT (t); predicted output curve P of photovoltaic power station pre,PV (t)。
3. The method for optimal configuration of a multi-energy complementary power supply base according to claim 1, wherein in step S3, the operation constraints of the wind farm and the photovoltaic power plant are expressed as:
wherein ,vh 、I h Wind speed at time hAnd illumination intensity;
respectively representing power characteristic conversion functions of wind power and photovoltaic; />
Respectively representing the abandoned wind and the abandoned light power of the power plant i at the time h; omega shape WT 、Ω PV Representing a collection of wind farms and photovoltaic power plants, respectively.
4. The method for optimal configuration of a multi-energy complementary power supply base according to claim 1, wherein in step S3, capacity characteristics are expressed as:
wherein ,CapCPP,credit Is the confidence capacity of the composite power station; b (B) peak Is a set of peak-to-load periods; t (T) peak Is the duration of the peak charge period;
the charge characteristics are expressed as:
wherein ,ECPP Generating power of the composite power station in the simulation period;
reliability is expressed as:
wherein ,XCPP The output state variable is the output state variable of the composite power station;
representing the s-th output state of the composite power station; />
Indicating the output state of the composite power station as +.>
Probability of (2); NS (NS) CPP The number of output states of the composite power station; />
Flexibility includes:
climbing capacity, specifically:
wherein ,Bup A set representing a load rising period; t (T) up A length indicating a load rising period;
climbing ability, in particular
wherein ,Bdown A set representing a load-down period; t (T) down A length representing a load-falling period;
providing positive standby capability, specifically:
wherein ,Bpeak A set representing load peak-to-load periods; t (T) peak Representing the length of the load peak-to-load period; omega shape FP Representing a set of flexible power plants;
representing the maximum output force which can be provided by the ith power plant at the time h;
providing negative standby capability, specifically:
wherein ,Bvalley Representing a set of load valley periods; t (T) valley Representing the length of the load valley period;
representing the minimum output force which can be provided by the ith power plant at the time h;
the environmental protection is as follows:
wherein ,
representing the emission of the composite plant pollutant x during the simulation period; omega shape F Is a collection of fuel power sources; f (P) i,h ) A fuel consumption characteristic function of the power plant i; o (O) i,x Is the emission equivalent of the pollutant x of the power plant i.
5. The method for optimal configuration of a multi-energy complementary power supply base according to claim 1, wherein in step S4, the solving result includes: the method comprises the steps of generating a unit production scheme of each power plant to be selected in a composite power station, generating power of each power plant in the composite power station in a simulation period, and planning and running costs of the composite power station; after the exact configuration and operating strategy of the composite power station is obtained, the capacity characteristics, the electric quantity characteristics, the reliability, the flexibility and the environmental protection of the composite power station are calculated.
6. A computer readable storage medium storing one or more programs, wherein the one or more programs comprise instructions, which when executed by a computing device, cause the computing device to perform any of the methods of claims 1-5.
7. A computing device, comprising:
one or more processors, memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs comprising instructions for performing any of the methods of claims 1-5.
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